Title :
Challenge: Processing web texts for classifying job offers
Author :
Amato, Flora ; Boselli, Roberto ; Cesarini, Mirko ; Mercorio, Fabio ; Mezzanzanica, Mario ; Moscato, Vincenzo ; Persia, Fabio ; Picariello, Antonio
Author_Institution :
Dept. of Comput. Sci. & Syst., Univ. of Naples Federico II, Naples, Italy
Abstract :
Today the Web represents a rich source of labour market data for both public and private operators, as a growing number of job offers are advertised through Web portals and services. In this paper we apply and compare several techniques, namely explicit-rules, machine learning, and LDA-based algorithms to classify a real dataset of Web job offers collected from 12 heterogeneous sources against a standard classification system of occupations.
Keywords :
Web services; advertising; employment; labour resources; learning (artificial intelligence); pattern classification; portals; text analysis; LDA-based algorithms; Web portals; Web services; Web texts processing; explicit-rules; heterogeneous sources; job offers advertisement; job offers classification; labour market data; linear discriminant analysis; machine learning; occupations; private operators; public operators; standard classification system; Accuracy; Europe; Power capacitors; Static VAr compensators;
Conference_Titel :
Semantic Computing (ICSC), 2015 IEEE International Conference on
Conference_Location :
Anaheim, CA
DOI :
10.1109/ICOSC.2015.7050852
